Open ghost opened 4 years ago
Thanks for the comment. Yes, I think the omitting NaNs is sensible here.
Perhaps that should be the default behavior for gaverager.
I don't quite follow how that omitnan argument is having effect in rms2. Is there more to that function?
ERPLABV8: gaverager.m returns NaNs in the case that one of the subjects doesn't have epochs for one bin because of the line: 415- dq_rms = rms(dq_data_here,4);
Solved it with a different rms function that can omit NaNs: function out=rms2(A,varargin) out=sqrt(mean(A.^2,varargin{:})); end
and replacing the original line with: dq.data = rms2(dq_data_here,4,'omitnan');